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Improving Deep Reinforcement Learning through Interactive Human Feedback School of Computer Science PhD Research Project Directly Funded Students Worldwide Dr Bei Peng, Dr Robert Loftin Application
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Better Personalization of Deep Learning-Enhanced Hearing Devices - Royal National Institute for Deaf People (RNID) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD Research
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Better Personalization of Deep Learning-Enhanced Hearing Devices - Royal National Institute for Deaf People (RNID)
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Improving Deep Reinforcement Learning through Interactive Human Feedback
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Knowledge of machine learning or multi-omics data integration would be highly desirable Essential Application/Interview Deep interest in musculoskeletal research and translational science Essential
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Design of a Fault Detection System for AI-Assisted Adversarial Attacks on Industrial Control Systems
experimentation with advanced AI techniques like multi-agent deep reinforcement learning (MDRL), this project will contribute to securing next-generation industrial systems and critical infrastructure. Supervisor
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Knowledge of machine learning or multi-omics data integration would be highly desirable Essential Application/Interview Deep interest in musculoskeletal research and translational science Essential
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containing C9orf72 transcripts failed to provide clinical benefit, and in some cases caused greater clinical decline. The goal of this project is to utilise our deep mechanistic understanding of C9orf72
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Interview / Application Deep expertise in technology architecture including infrastructure, software and data environments. Essential Interview / Application Knowledge and experience of Cloud adoption
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, security and infrastructure technologies with deep knowledge in several areas. Essential Interview / Application Ability to drive customer-oriented design processes, producing architectural designs from